Genome-wide expression analysis has become a routine and powerful tool in biomedical research. However, extracting the full biological insight contained in such data remains a major challenge. Knowledge-based approaches have the potential to accelerate the interpretation of results and generation of hypotheses, which can then be experimentally validated. We have recently developed a powerful analytical method called Gene Set Enrichment Analysis (GSEA) for interpreting gene expression data. The method derives its power by focusing not on single genes, but on gene sets - that is, groups of genes that share common biological function, chromosomal location or regulation. GSEA has proven successful in providing insight into a variety of disease-related studies, including in diabetes and cancers. We have also created an initial resource, the Molecular Signatures Database (MSigDB), consisting of approximately 1300 annotated gene sets to be used with GSEA. The GSEA software and the MSigDB database are freely distributed as user-friendly, platform-independent software tools to bring the power of GSEA, available to the entire research community. In only 6 months since their informal release, over 200 users have downloaded the tools. The goal of this grant is to enhance the GSEA software and MSigDB database and to ensure their distribution to research community. The two specifics aims thus focus on: Aim 1. Enhancements to GSEA and MSigDB to Better Support Users and Their Research. Aim 2. Maintenance and User Support for GSEA and MSigDB. We have extensive experience in software engineering, including the development and distribution of the GenePattern software that is used by over 1300 scientists world-wide. We also have a solid history of producing successful user workshops and documentation. This, together with our initial GSEA user base, makes us well poised to carry out the aims of this proposal. [unreadable] [unreadable] [unreadable]